\name{createAdaptiveRandomWalkProposal}
\alias{createAdaptiveRandomWalkProposal}
\title{Adaptive Random Walk proposal distribution for MCMC algorithms}
\usage{
  createAdaptiveRandomWalkProposal(nchains,
    targetdimension, adaptiveproposal, adaptationrate,
    sigma_init)
}
\arguments{
  \item{nchains}{Object of class \code{"numeric"}: it
  should be an integer representing the desired number of
  parallel chains.}

  \item{targetdimension}{Object of class \code{"numeric"}:
  it should be an integer representing the dimension of the
  target distribution.}

  \item{adaptiveproposal}{Object of class \code{"logical"}:
  specifies whether an adaptive proposal (Robbins-Monroe
  type of adaptation) should be used. Default is FALSE.}

  \item{adaptationrate}{Object of class \code{"function"}:
  specifies the rate at which the adaptation of the
  proposal is performed. It should be a function defined on
  [0, + infty[ such that it is not integrable but its
  square is integrable, e.g. t -> 1/t for instance. The
  default is t -> t^-0.6.}

  \item{sigma_init}{Object of class \code{"numeric"}: it
  should be a positive real number specifying the standard
  deviation of the proposal distribution at the first
  iteration. If the proposal is adaptive, it acts as a
  starting point for the adaptation. If it is not adaptive,
  then this value is used throughout all the iterations.
  Default is 1.}
}
\value{
  The function returns an object of class
  \code{\link{proposal-class}}, to be used in calls to
  \code{\link{adaptiveMH}} and \code{\link{pawl}}.
}
\description{
  Create the adaptive gaussian random walk proposal that is
  used as a default in \code{\link{adaptiveMH}} and
  \code{\link{pawl}}, whenever the target distribution is
  continuous.
}
\author{
  Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob
  <pierre.jacob.work@gmail.com>
}
\seealso{
  \code{\link{proposal-class}}, \code{\link{adaptiveMH}},
  \code{\link{pawl}}
}

